class_docstr: A class for checking if a neural network satisfies constraints. 
docstr: Constructor. 
docstr_tok: ["Constructor","."]
code: def __init__(
      self,
      max_num_layers,
      min_num_layers,
      max_mass,
      min_mass,
      max_in_degree,
      max_out_degree,
      max_num_edges,
      max_num_units_per_layer,
      min_num_units_per_layer,
  ):
      """Constructor."""
      super(NNConstraintChecker, self).__init__()
      self.max_num_layers = max_num_layers
      self.min_num_layers = min_num_layers
      self.max_mass = max_mass
      self.min_mass = min_mass
      self.max_in_degree = max_in_degree
      self.max_out_degree = max_out_degree
      self.max_num_edges = max_num_edges
      self.max_num_units_per_layer = max_num_units_per_layer
      self.min_num_units_per_layer = min_num_units_per_layer
      self.constraint_names = [
          "max_num_layers",
          "min_num_layers",
          "max_mass",
          "min_mass",
          "max_in_degree",
          "max_out_degree",
          "max_num_edges",
          "max_num_units_per_layer",
          "min_num_units_per_layer",
      ]
  
imports: import numpy
  from copy import copy
  from ..exd.domains import Domain
label_desc: Use image node_id 1 to create a new NNConstraintChecker object from inherited base classes: object with example: obj = NNConstraintChecker(max_num_layers, min_num_layers, max_mass, min_mass, max_in_degree, max_out_degree, max_num_edges, max_num_units_per_layer, min_num_units_per_layer)